摘要
考虑一类扰动可测的离散时间多变量线性系统,提出一种稳定化增量模型预测控制(MPC)算法。以控制增量状态空间模型作为预测模型,定义MPC的有限时域最优控制问题,得到具有可测扰动前馈-时滞状态反馈结构的MPC控制器。进一步,利用时滞系统(Lyapunov-Krasovskii,L-K)稳定性理论,建立无约束闭环预测控制系统的稳定性充分条件。最后通过对约束平面轮廓控制系统进行仿真控制研究,仿真结果验证了所提出算法的正确性和有效性。
This paper presents a stabilizing incremental model predictive control(MPC) algorithm for discrete-time multivariable linear systems with measurable disturbances. Taking the incremental state-space model as the predictive model, the finite horizon optimal control problem of MPC is formulated and the corresponding MPC controller is determined, which has a structure combining measurable disturbance feedforward with time-delay state feedback. Using the Lyapunov-Krasovskii stability theory of time-delay systems, we establish some sufficient conditions guaranteeing the stability of the closed-loop system with no constraints. Finally, the simulation example of a constrained biaxial contouring control system is employed to illustrate the validity of the algorithm proposed here.
作者
张全鹏
何德峰
吴赛男
余世明
ZHANG Quan-peng;HE De-feng;WU Sai-nan;YU Shi-ming(College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China)
出处
《控制工程》
CSCD
北大核心
2019年第2期258-263,共6页
Control Engineering of China
基金
国家自然科学基金(61374111
61773345)
浙江省公益技术应用研究计划项目(GB15021030011)
关键词
模型预测控制
多变量控制
稳定性
时滞
轮廓控制
Model predictive control
multivariable control
stability
time-delay
contour control
